Data has unique features as a commodity that make data markets distinct from other markets. First, in some cases data is traded for other data (bilateral sharing) as opposed to an exchange of data for money (unilateral sharing). In bilateral sharing, the agents gain access to each others' data. Bilateral sharing is natural in use cases in which it is hard to evaluate and attach a price to data [1]}. Indeed, the fundamental challenge of quantifying the value of data in algorithmic predictions and decision-making is an active research area [2]}, [1]}. It is also natural when regulations do not permit the exchange of money for data; this would be the case for the sharing of patient data. Bilateral trade without money also arises in other markets. Companies exchange their pool of patents with each other because they can not evaluate and attach a price to their patent pool. Also, regulatory limits on trading commodities with money also exist for various forms of matching markets, including kidney exchange markets. Relationships, such as friendships or marriage, are other forms of markets with bilateral exchange where money is not used. Even within the context of such examples, however, data markets are distinct. In particular, data is traded often at some privacy and communication cost for agents (in contrast to patent market) and one agent can share data with multiple agents through bilateral exchanges (in contrast to organ donation or marriage markets).
